Cargando…
An improved prognostic model for predicting the mortality of critically ill patients: a retrospective cohort study
A simple prognostic model is needed for ICU patients. This study aimed to construct a modified prognostic model using easy-to-use indexes for prediction of the 28-day mortality of critically ill patients. Clinical information of ICU patients included in the Medical Information Mart for Intensive Car...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9744859/ https://www.ncbi.nlm.nih.gov/pubmed/36509888 http://dx.doi.org/10.1038/s41598-022-26086-1 |
_version_ | 1784849018780647424 |
---|---|
author | Zhang, Xianming Yang, Rui Tan, Yuanfei Zhou, Yaoliang Lu, Biyun Ji, Xiaoying Chen, Hongda Cai, Jinwen |
author_facet | Zhang, Xianming Yang, Rui Tan, Yuanfei Zhou, Yaoliang Lu, Biyun Ji, Xiaoying Chen, Hongda Cai, Jinwen |
author_sort | Zhang, Xianming |
collection | PubMed |
description | A simple prognostic model is needed for ICU patients. This study aimed to construct a modified prognostic model using easy-to-use indexes for prediction of the 28-day mortality of critically ill patients. Clinical information of ICU patients included in the Medical Information Mart for Intensive Care III (MIMIC-III) database were collected. After identifying independent risk factors for 28-day mortality, an improved mortality prediction model (mionl-MEWS) was constructed with multivariate logistic regression. We evaluated the predictive performance of mionl-MEWS using area under the receiver operating characteristic curve (AUROC), internal validation and fivefold cross validation. A nomogram was used for rapid calculation of predicted risks. A total of 51,121 patients were included with 34,081 patients in the development cohort and 17,040 patients in the validation cohort (17,040 patients). Six predictors, including Modified Early Warning Score, neutrophil-to-lymphocyte ratio, lactate, international normalized ratio, osmolarity level and metastatic cancer were integrated to construct the mionl-MEWS model with AUROC of 0.717 and 0.908 for the development and validation cohorts respectively. The mionl-MEWS model showed good validation capacities with clinical utility. The developed mionl-MEWS model yielded good predictive value for prediction of 28-day mortality in critically ill patients for assisting decision-making in ICU patients. |
format | Online Article Text |
id | pubmed-9744859 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-97448592022-12-14 An improved prognostic model for predicting the mortality of critically ill patients: a retrospective cohort study Zhang, Xianming Yang, Rui Tan, Yuanfei Zhou, Yaoliang Lu, Biyun Ji, Xiaoying Chen, Hongda Cai, Jinwen Sci Rep Article A simple prognostic model is needed for ICU patients. This study aimed to construct a modified prognostic model using easy-to-use indexes for prediction of the 28-day mortality of critically ill patients. Clinical information of ICU patients included in the Medical Information Mart for Intensive Care III (MIMIC-III) database were collected. After identifying independent risk factors for 28-day mortality, an improved mortality prediction model (mionl-MEWS) was constructed with multivariate logistic regression. We evaluated the predictive performance of mionl-MEWS using area under the receiver operating characteristic curve (AUROC), internal validation and fivefold cross validation. A nomogram was used for rapid calculation of predicted risks. A total of 51,121 patients were included with 34,081 patients in the development cohort and 17,040 patients in the validation cohort (17,040 patients). Six predictors, including Modified Early Warning Score, neutrophil-to-lymphocyte ratio, lactate, international normalized ratio, osmolarity level and metastatic cancer were integrated to construct the mionl-MEWS model with AUROC of 0.717 and 0.908 for the development and validation cohorts respectively. The mionl-MEWS model showed good validation capacities with clinical utility. The developed mionl-MEWS model yielded good predictive value for prediction of 28-day mortality in critically ill patients for assisting decision-making in ICU patients. Nature Publishing Group UK 2022-12-12 /pmc/articles/PMC9744859/ /pubmed/36509888 http://dx.doi.org/10.1038/s41598-022-26086-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Zhang, Xianming Yang, Rui Tan, Yuanfei Zhou, Yaoliang Lu, Biyun Ji, Xiaoying Chen, Hongda Cai, Jinwen An improved prognostic model for predicting the mortality of critically ill patients: a retrospective cohort study |
title | An improved prognostic model for predicting the mortality of critically ill patients: a retrospective cohort study |
title_full | An improved prognostic model for predicting the mortality of critically ill patients: a retrospective cohort study |
title_fullStr | An improved prognostic model for predicting the mortality of critically ill patients: a retrospective cohort study |
title_full_unstemmed | An improved prognostic model for predicting the mortality of critically ill patients: a retrospective cohort study |
title_short | An improved prognostic model for predicting the mortality of critically ill patients: a retrospective cohort study |
title_sort | improved prognostic model for predicting the mortality of critically ill patients: a retrospective cohort study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9744859/ https://www.ncbi.nlm.nih.gov/pubmed/36509888 http://dx.doi.org/10.1038/s41598-022-26086-1 |
work_keys_str_mv | AT zhangxianming animprovedprognosticmodelforpredictingthemortalityofcriticallyillpatientsaretrospectivecohortstudy AT yangrui animprovedprognosticmodelforpredictingthemortalityofcriticallyillpatientsaretrospectivecohortstudy AT tanyuanfei animprovedprognosticmodelforpredictingthemortalityofcriticallyillpatientsaretrospectivecohortstudy AT zhouyaoliang animprovedprognosticmodelforpredictingthemortalityofcriticallyillpatientsaretrospectivecohortstudy AT lubiyun animprovedprognosticmodelforpredictingthemortalityofcriticallyillpatientsaretrospectivecohortstudy AT jixiaoying animprovedprognosticmodelforpredictingthemortalityofcriticallyillpatientsaretrospectivecohortstudy AT chenhongda animprovedprognosticmodelforpredictingthemortalityofcriticallyillpatientsaretrospectivecohortstudy AT caijinwen animprovedprognosticmodelforpredictingthemortalityofcriticallyillpatientsaretrospectivecohortstudy AT zhangxianming improvedprognosticmodelforpredictingthemortalityofcriticallyillpatientsaretrospectivecohortstudy AT yangrui improvedprognosticmodelforpredictingthemortalityofcriticallyillpatientsaretrospectivecohortstudy AT tanyuanfei improvedprognosticmodelforpredictingthemortalityofcriticallyillpatientsaretrospectivecohortstudy AT zhouyaoliang improvedprognosticmodelforpredictingthemortalityofcriticallyillpatientsaretrospectivecohortstudy AT lubiyun improvedprognosticmodelforpredictingthemortalityofcriticallyillpatientsaretrospectivecohortstudy AT jixiaoying improvedprognosticmodelforpredictingthemortalityofcriticallyillpatientsaretrospectivecohortstudy AT chenhongda improvedprognosticmodelforpredictingthemortalityofcriticallyillpatientsaretrospectivecohortstudy AT caijinwen improvedprognosticmodelforpredictingthemortalityofcriticallyillpatientsaretrospectivecohortstudy |